A fast charging and an accurate battery State of Charge (SoC) and State of Health (SoH) estimation method are essential for having optimum utilisation of a battery energy storage system (BESS). Both are considered as key aspects of an advanced battery management system (BMS) for any green technology application, including future vehicles. The proper method of charging is to extend the battery life, decrease the charging time and prevent it from potential damage from being overcharged. An accurate and reliable SoC and SoH estimation is important for user convenience, safety, and battery performance. Accurate knowledge of BESS profile is the starting point to build a fast charger and advanced BMS. Investigating the operation algorithm of typical 12V VRLA battery charger and compare two basic SoC estimation methods are the two main objectives of this thesis. This thesis summarises the research work of the MPhil project 'Profile of 12-V Voltage-Regulated Lead-Acid Battery (VRLAB) during Charge and Discharge Operation'. Three different capacities of VRLAB were tested using a commercial charger and four different discharge rates. Experiment results were analysed and the SoC-SoH of the batteries were estimated based on full discharge test and coulomb counting method. The commercial charger control algorithm is a three-step PWM charging method (constant current /CC, constant voltage /CV and floating voltage /FV). The battery voltage (Vbat) profile of each VRLAB during charging was highly affected by the initial and the historical Vbat of the previous BESS operation. The Vbat average increased rate and Ibat average decreased rate during the CC and CV charging period, which were 0.23V/h and 0.05A/h, respectively. The SoH (represent Qmax) of the battery decreases as the battery cycle increases (ageing), as shown in the last experiment result with an error of 10%. IEEE standard for VRLA is used to test the battery performance by discharge test based on time discharge (tdis) and discharge rate variables.